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Educators professional inventory sample questions

Educators professional inventory sample questions

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Table of Contents 1.A Brief Introduction to Don 2.Video: Is there a Moneyball for Teachers? 3.Introduction to Research: A Basic Overview 4.Resume the Roulette Game 5.Digging a Little Deeper into the Research and Applying It to Hiring and Student Achievement 6.Taking the Following Step
The Most Important Factor Is Teachers However, there has been very little work put into ensuring that they are recruited with scientific accuracy. Is it possible to predict the success of teacher candidates? Yes, indeed! The Educational Performance Index (EPI) is the first and only comprehensive instrument that predicts the effect of teachers on student achievement. And, thanks to advanced machine learning capabilities, the longer it is in operation, the better it gets.
Roulette for your resume 1.Split up into small groups. 2.Look at your stack of resumes and choose two candidates to interview right away. 3.After that, make a list of the top three criteria that everyone in the community agrees are the most appropriate for making these decisions. 4.Choose a speaker who can easily introduce the two people and the criteria.
Automating a process Analytical Excellence Hierarchical Linear Modeling (HLM): Determines which EPI items are most predictive of student development. HLM and VAM reports are used to deliver the EPI, which is used to test candidates and report on their results. Modeling for Value-Add: Our organizational concept of “teacher effectiveness” was used as a Dependent Variable in our HLM model. EPI is a genuinely multidisciplinary project. We put together experts from various fields that would not necessarily interact.

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The most recent advancement in teacher hiring: a method of determining a teacher’s effectiveness before he or she even enters the classroom.

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TeacherMatch, a Chicago-based organization that specializes in data-driven recruiting practices, believes that its predictive analytics tools can classify high-quality teacher applicants and help optimize the recruitment process, reducing teacher attrition and absenteeism, as well as helping to address teacher shortages, according to experts.

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The Educators Professional Inventory, or EPI, is the company’s most well-known method, and it’s designed to predict how new teacher hires will affect student achievement. The EPI evaluates candidates’ responses to a 90-minute questionnaire and places a strong emphasis on four “performance indicators”: credentials, teaching abilities, attitude variables, and cognitive capacity.
Using data-driven software helped the Shelby County district in Memphis, Tenn. estimate the number of vacancies likely to open at the end of the year, and thus inform recruiting and staffing strategies, according to an Education Week special report story published in January. Meanwhile, Deerfield Public Schools District 109 in Deerfield, Illinois, used data from a number of data-driven tests to show that 85 percent of the staff it recruited for the 2014-15 school year had a positive effect on students. Data collection and analysis can also aid in increasing organizational diversity; the Cleveland school district used this approach to raise the number of teachers of color from 25% to 34%. “As recruiting becomes more competitive and talent management becomes more strategic, districts are realizing the need to pursue the most tested, creative solutions available,” said Kermit Randa, CEO of PeopleAdmin. “Today, no district, big or small, can afford to make a recruiting mistake when it comes to educators. They don’t have to anymore.” More on teacher recruitment and data:

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I recently applied to the Downey Unified School District in Southern California and was directed to the Teachermatch website to take the “EPI” test to determine if I was a good fit. It was a strange, poorly-written exam that made me furious that school districts are paying this company tens of thousands of dollars for these fake, pointless candidate tests.
It lasted an hour and a half and consisted of timed questions on reasoning, analogies, math, philosophy, hypothetical scenarios, and other topics. Many of the questions are multiple choice. Several questions about educational theory had no options that represented my philosophy, so I had to choose one to pass on to the next. There was a question about multiplying fractions (not a word problem, but simply 3/5 X 2/3), with fractions preceded by abbreviations I had never seen before (ie “3/4 nf” and “1/2 bd”), but no correct answer. I graduated from UC San Diego, which is regularly ranked as one of the best universities in the world. Those abbreviations were foreign to me. However, in order to move on to the next question, you must choose an answer. And you just have 90 seconds to pick, or you’ll be numbered “in violation.”

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In an attempt to increase the pipeline of new teachers, the Obama administration has suggested cutting funds from ineffective teacher training programs. However, school districts are not waiting for the federal government to step in.
Instead, they’re gradually turning to consulting firms that promise to use Big Data in a “Moneyball”-style approach to classify potential superstar educators from a pool of thousands of candidates.
The latest screening tools cut and dice prospective teachers into hundreds of data points, ranging from SAT scores to art appreciation to geometric pattern completion. All of this information is then fed into an algorithm, which generates a score that predicts the probability of each candidate being a successful teacher — or, at the very least, raising students’ math and reading scores.
Christine Smith, human resources director for the Red Clay Consolidated School District in Delaware, which is testing a data-driven screening system, said, “We’re pretty excited.” “We hope that by using this method, we will be able to remove some of the subjectivity from our hiring process and adopt a more scientific approach.”